![]() Z-Value basically tells us how many standard deviation away from mean is the observed value. To find p-value we must first find Z-value. But if this value is low, then we say that it is highly unlikely that observed value came out to be lesser than 70 just by random chance and we reject the null hypothesis.īut this p-value is quite elusive. So, if this value is higher, then we say that it is just random chance that x<70, and we ‘fail to reject null hypothesis’. Assuming null hypothesis is true (remember, innocent until proven guilty), It tells us what is the probability that observed value comes out to be lesser than 70 just by random chance. ![]() P-value is simply the Random Chance Probability value. Now, We need evidence to Reject our null hypothesis. Now that we have plotted all the sample means, what next? This is true in all cases (check out 68-95-99.7 Rule) Here μ refers to the Mean and σ refers to the Standard Deviation. It could be because we haven’t looked at the right place! We don’t say that H 0 is True just because we have not found suitable evidence. But what if we don’t find any evidence to support our claim? In that case, we say that we have ‘Failed to Reject the null hypothesis’. #Parameter elimination by sequential testing trialRight now H 0 is on trial and we have to provide evidence to reject the null hypothesis H 0. It is the prosecutors job to prove that accused is guilty. H a: Students score an average lesser than 70%.Īt first, H 0 is assumed to be true just like how an accused in a court trial is innocent until proven guilty. ![]() H 0: Students score an average of 70% or more Your teacher says that students score an average of 70% or more and you want to prove that it is total rubbish and that it is way lesser than that.Īs a general rule, we set null hypothesis (H 0) to be the opposite of what we want to test and alternate hypothesis(H a) to be what we want to test. Hypothesis is nothing but an assumption which has not been tested yet and Hypothesis Testing is simply checking if that assumption is correct or not. The folks who already know about this can jump to the good stuff right away!. ![]() Now some of you who are wondering what is Hypothesis Testing, p-value and null hypothesis in the above definition of p-value by Wikipedia. In statistical hypothesis testing, the p– value or probability value is the probability of obtaining test results at least as extreme as the results actually observed during the test, assuming that the null hypothesis is correct. ![]()
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